Science1 publisher2 min readPublished
Variants that carry chromatin changes through to expression colocalize with disease twice as often
FinnGen's atlas of 10 million blood cells from 1,108 Finns finds full-cascade variants colocalize with disease at twice the chromatin-only rate. The result gives labs a way to rank which non-coding disease hits to test first, at least in circulating immune cells.
The Scientist · Science desk
Drafted by a language model from the sources cited here and checked against its claim ledger before publication. How we use AISend a correction
What happened
- The atlas maps 338,100 chromatin-accessibility QTLs across 210,584 peaks and 51,083 expression QTLs for 20,829 genes, about 6.6 chromatin QTLs per expression QTL.
- The team nominated 119,094 putative causal variants and called 593,765 links between accessible chromatin peaks and genes.
- At evolutionarily constrained genes, chromatin changes keep normal effect sizes, but their effect on expression is weakened and spread across weaker, more numerous enhancer-gene links.
- Worked examples include cascades at the autoimmune loci TICAM1 and RHOH and at Finnish-enriched variants in TNRC18 and IL21R.
Compiled by The ScientistSomething wrong?How this is made
Why it matters
- decision Follow-up work on disease hits at constrained genes needs a chromatin readout, because an expression-only assay there will understate a variant whose effect is damped on its way to the transcript.
- capability Any group can check whether a variant it cares about completes a chromatin-to-expression cascade in blood immune cells, using the public summary statistics and the cascade.finngen.fi browser.
- constraint Independent reanalysis at the level of single cells requires an approved application through Findata, Fingenious or the Blood Service Biobank, because Finnish and EU rules bar redistribution of individual data.
Most disease-associated variants sit in non-coding DNA [1], so the first question about any such hit is what it does to gene regulation. Single-cell QTL mapping can link variants to regulation, but the authors write that it has lacked the power and the simultaneous measurements to trace a mechanism from chromatin to expression [2]. This study measured both layers in the same nuclei [3]. Each donor contributed about 9,000 cells on average [1].
Pairing the two readouts is what allows the comparison behind the doubling. Variants that alter accessibility and then expression colocalize with disease at twice the rate of variants that alter accessibility alone [7]. The abstract reports that ratio without the underlying colocalization rates. It also reports 10,428 fine-mapped QTLs validated in massively parallel reporter assays [8] without saying how many were tested. From here, a doubling of a small rate looks the same as a doubling of a large one, and no validation rate can be calculated. The sample is also one population and one compartment: circulating immune cells from Finnish donors [3]. I'd treat the doubling as a way to order candidates for follow-up in blood cells.
The buffering result is the most satisfying finding in the paper. Disease variants preferentially target evolutionarily constrained genes, yet expression QTL studies find those genes depleted of effects, and the authors say their data reconcile the two [10]. If a variant's chromatin effect is damped before it reaches the transcript, an expression-only scan would pick it up only weakly even though it sits at a disease locus. The team then asked where the damping happens. A reporter assay placed it downstream of the regulatory element, at the interface between chromatin and expression [11]. Constraint had not reduced the elements' intrinsic regulatory activity, which rules out the simplest alternative explanation: that constrained genes just have weaker enhancers [11].
The authors describe the atlas as a source of testable hypotheses for more than half of immune disease associations [12]. In my view that is the right level of confidence. The reporter assays confirm regulatory effects at the variant level [8]. The step from a completed cascade to disease still rests on statistical colocalization [7].
What to watch
- Publication of the absolute colocalization rates for cascade-completing and chromatin-only variants, which would show how large the doubling is in real terms.
- Replication of the cascade enrichment in tissue-resident immune cells or in non-Finnish cohorts.
- Perturbation experiments in native cells at the TICAM1, RHOH, TNRC18 and IL21R cascades that test the disease link directly.